The background description provided herein is for the purpose of generally presenting the context of the disclosure. Work of the presently named inventors, to the extent the work is described in this background section, as well as aspects of the description that may not otherwise qualify as prior art at the time of filing, are neither expressly nor impliedly admitted as prior art against the present disclosure.
Clinical identification of inflammatory bowel disease is performed based on clinical symptoms (which are largely subjective), with confirmation using an endoscopy and/or colonoscopy with tissue biopsy. However, these techniques have limited access to areas of the small bowel, carry a risk of perforation, and don't provide an accurate assessment of disease severity. While magnetic resonance enterography is one of the best non-invasive imaging technologies for evaluating inflammatory bowel disease, its interpretation remains subjective and variable, especially when it comes to assessing the severity of inflammatory bowel disease in the small bowel. Thus this invention addresses the creation of computer-aided diagnosis and decision support systems to assess presence and severity of inflammatory bowel disease.
Crohn's Disease Activity Index (CDAI), as described by Best et al. in “Development of a Crohn's Disease Activity Index”, National Cooperative Crohn's Disease Study, Gastroenterology 70, 439-444 (1976), and incorporated by reference in its entirety, is a symptom-based score used to quantify the symptoms of patients with Crohn's disease. The CDAI is a single index that is used for assessing a variety of therapies in Crohn's disease. Specifically, CDAI combines eight different clinical variables in its computation and is usually based on averaging scores over the course of a week. Thus, due to its dependency on a large time-interval (such as a week or the like), the use of the CDAI index has been limited to the realm of clinical trials. Additionally, a widely acknowledged limitation of the CDAI technique is lack of specificity, and as a result, experts support the notion of replacing the CDAI technique to quantify Crohn's disease by a robust alternative.
A non-invasive technique for developing disease indexes, proposed by Steward et al. in “Non-Perforating Small Bowel Crohn's Disease Assessed by MRI Enterography: Derivation and Histopathological Validation of an MR-based Activity Index”, European Journal of Radiology, v. 81 (9), 2080-2088 (2012), and incorporated herein by reference in its entirety, is a magnetic resonance based index of luminal small bowel Crohn's disease activity. However, in the technique used by Stewart, only breath-hold examinations are considered, and no motility information is included in the formulation of the disease index that uses only manual measurements of the mural thickness.
A technique to quantify different grades of bowel motility in patients using non-rigid registration and intensity changes was proposed by Odille et al. in “Quantitative Assessment of Small Bowel Motility by Non-rigid Registration of Dynamic MR Images”, Magnetic Resonance in Medicine vol. 68. 783-793 (2012), and is incorporated by reference in its entirety. However, in the technique proposed by Odille, only breath-hold cine magnetic resonance imaging was considered thereby limiting the potential applicability of the method. Furthermore, the proposed technique did not provide any structural information of the bowel.
In a similar work, proposed by Hamy et al. in “Respiratory Motion Correction in Dynamic-MRI: Application to Small Bowel Motility Quantification during Free Breathing”, Medical Image Computing and Computer-Assisted Intervention—MICCAI; vol. 2. 132-140 (2013), and incorporated by reference in its entirety, a technique of respiratory motion correction in free-breathing sequences was proposed. Specifically, the technique used an iterative registration method based on principal component analysis to compensate for the breathing movements of the patient. However, the resulting peristaltic activity maps that were created provided only qualitative information, rather than an objective measurement of the intestinal activity, e.g. in millimeters per second. Moreover, the proposed technique of Hamy did not provide any structural information of the bowel.
Farghal et al. proposed a method “Developing a new measure of small bowel peristalsis with dynamic MR: a proof of concept study”, Acta-Radiologica vol. 53 593-600 (2012), and incorporated by reference in its entirety, to estimate a parametric map for small bowel peristalsis in breath-hold dynamic MR images. The method estimated the motility of the small bowel by means of the mean change in signal amplitude. However, the method of Farghal did not describe or consider any structural information of the bowel.
Additionally, Schuffler et al., proposed a technique based on magnetic resonance imaging in “A Model Development Pipeline for Crohn's Disease Severity Assessment from Magnetic Resonance Images”, MICCAI Workshop on Abdominal Imaging: Computational Challenges and Clinical Applications, (2013), and incorporated by reference in its entirety, to assess the severity of Crohn's disease in the intestinal tract. The proposed technique employed machine learning approaches to quantify disease severity. However, the predictive features were manually defined by the clinical expert, and the use of dynamic MRI sequences was not described or considered. Furthermore, the motility of the small bowel was not considered as a predictive feature.
Furthermore, in the work of Froechlich J. M., et al. “MR motility imaging in Crohn's disease improves lesion detection compared with standard MR imaging,” Gastrointestinal, 20 (8), 2010, incorporated by reference in its entirety, and the work of Menys, A., et al. “Quantified terminal ideal motility during MR enterography as a potential biomarker of Crohn's disease activity: a preliminary study,” Gastrointestinal, 22(11), 2012, and incorporated herein by reference in its entirety, it has been shown that motility (peristaltic activity) of the small bowel correlates with the severity of inflammatory bowel disease.
Accordingly, there is a requirement for assessing and characterizing inflammatory bowel disease by merging and quantifying anatomical and structural information of the small bowel with the quantification of peristaltic activity in order to facilitate accurate and objective diagnosis, monitor efficacy of treatment, evaluate new medical therapies, and thus ensure more directed treatment in inflammatory bowel disease.